8.18.2011

IBM's first cognitive computing chips mimic functions of the brain

Today, IBM announced the very first cognitive computing chips, designed to emulate the brain’s abilities for perception, action and cognition. The technology could yield many orders of magnitude less power consumption and space than used in today’s computers, and give computers a sort of "right brain" capability to match their superior calculating abilities. Following Watson, it is yet another example of IBM's quest to build learning systems.

The Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) project is driven from funding by the Defense Advanced Research Projects Agency's (DARPA); and entering Phase 2 of the SyNAPSE project (Phases 0 and 1 are complete), IBM has built two state-of-the-art chips unlike anything produced before. These chips defy the traditional von Neumann architecture, which relies on programs or instructions to complete these tasks. IBM will use these chips as the basis for an architecture with no set programming.

A peek inside IBM's brain lab in San Jose, CA:

SyNAPSE technical project manager Bill Risk next to the "brain wall." Each of the yellow boxes represents one of the cognitive computing chips (256 neurons), and close up you'll see them blinking - these are neurons firing.

IBM researchers Paul Merolla (left) and John Arthur having fun firing up a SyNAPSE demo.

10 things to know about SyNAPSE

1. The brain uses less energy than a 25 watt light bulb and occupies less volume than a 2-liter bottle of soda -- capable of completing complex tasks, while autonomously computing what it needs to, and when, and knowing what information to save and for how long. The brain is the ultimate computer.

A cognitive computing system monitoring the world's oceans could contain a network of sensors and actuators that constantly record and report metrics such as temperature, pressure, wave height, acoustics and ocean tide, and issue tsunami warnings based on its decision making. Similarly, a grocer stocking store shelves could use an instrumented glove that monitors sights, smells, texture and temperature to flag bad or contaminated produce.

2. Today's computers use an architecture that was designed 40 years ago. Without using more power and taking up more space, we simply can't program today's computers to do the tasks that are required to handle the growing mountains of data we are faced with.

3. Cognitive computers emulate the brain’s abilities for sensation, perception, action, interaction and cognition, while integrating and analyzing vast amounts of data from many sources at once: in essence the "right brain" to today's "left brain" computers.

4. These systems won’t be programmed like traditional computers are today. Rather, cognitive computers will learn dynamically through experiences, find correlations, create hypotheses and remember – and learn from – the outcomes, emulating the human brain’s synaptic and structural plasticity (or the brain's ability to re-wire itself over time as it learns and responds to experiences and interactions with its environment.)

5. To accomplish this new kind of system, IBM is combining neuroscience, nanoscience and supercomputing together to rival the function, power and space of the brain.

6. Supercomputing: In November 2009, scientists used an IBM Blue Gene supercomputer to achieve significant advances in large-scale cortical simulation of a cat brain, substantiating the feasibility of a cognitive computing chip.

7. Neuroscience: Last year, scientists here at Almaden uncovered and successfully mapped the largest long-distance network of the monkey brain, which is essential for understanding the brain’s behavior, complexity, dynamics and computation. This discovery gives scientists unprecedented insight into how information travels and is stored across the brain.

8. Nanoscience: The revolutionary new chip that we've unveiled is a building block towards the long-term goal of SyNAPSE; to build a chip system with ten billion neurons and hundred trillion synapses, while consuming merely one kilowatt of power and occupying less than two liters of volume.

9. Computers like this could have a significant impact on virtually every sector of the economy. The application and service possibilities will range from preventing fraud and providing better security, to helping scientists better understand intricate climate changes happening to our planet (see callout text).

10. IBM has assembled a world-class team including collaborators from Cornell University, Columbia University, University of California - Merced and University of Wisconsin - Madison, to work with their scientists from IBM Research sites including Austin, TX, Yorktown Heights, NY, India and Zurich.

17 comments:

Your lede / title is just misleading. Where's the description of how the chip learned to play pong? It jumps straight into describing something else which seems only tangentially related. You're missing the story for the facts. Honestly, this is poor writing; we should acknowledge and fix that.

the way this is hyped is rather embarrassing. Nothing wrong with the goal of making better chips and computers, but the last time I checked, we had not yet figured out how the brain works. So how can we emulate it?

In 2009 33,800 persons died on American highways. Question: Is the Electronic CognitiveAutomobile a possibility given the technological, economic and political climate in the U.S.? Interested in your thoughts. Bigthumbs up to IBM.

"The way this is hyped is rather embarrassing. Nothing wrong with the goal of making better chips and computers, but the last time I checked, we had not yet figured out how the brain works. So how can we emulate it?"

We do not yet know the precise algorithms of the brain, however, we do know a great deal about its basic building blocks, which include neurons, axons, and synapses. Our chips run extremely efficient digital models of these basic components, and allow us to map brain-like networks to perform tasks like recognition, control, and sensory integration. The important distinction is that we are not attempting to reverse engineer biological neural systems cell by cell; rather, we are interested in drawing inspiration from the brain's architecture so that we can capture its incredible efficiency.

Anonymous said...Won't the silicon to carbon revolution be 'bigger' than this?

I am not sure if you talking about the revolution to silicon carbide, carbon nanotubes, graphene, or some other technology, but in any case what we have built is an architecture not strongly tied to the underlying implementation technology. Brains use a similar architecture using wetware components (neurons, synapses, and axons), and we built ours using silicon, constructing analogs of these components from transistors.

The architecture and behavior of the chip are inspired by the brain's structure and function, and as such we researchers drew a great deal from existing neuroscience knowledge and literature. We are not doing animal experiments in this work, nor did any animal experiments drive this research.